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November 2026. I’m hiring! We are looking for researchers/engineers to work on data-driven RSI (recursive self-improvement). Candidates with a background in LLM post-training or model inference acceleration/optimization are welcome to contact me at wubeen@outlook.com.
Bin Wu ☕️

Bin Wu

Research Scientist / Senior Technology Research Expert

Database and Storage Lab, Alibaba Cloud

Biography

Bin Wu is a Research Scientist / Senior Technology Research Expert at the Database and Storage Lab at Alibaba Cloud. His work centers on driving innovation from Data+AI research to production, where he develops novel methods for top-tier conferences and deploys them at scale to solve critical business challenges. His current research focuses on Agentic RAG, NL2SQL, and AI Agents. Additionally, his research interests include theoretical computer science and large-scale database management systems.

Previously, he was a researcher at Huawei’s Noah’s Ark Lab. He received his Ph.D. in Computer Science from The Hong Kong University of Science and Technology (HKUST) in 2017, supervised by Prof. Ke Yi, and his bachelor’s degree from Fudan University in 2012. He is a recipient of the ACM SIGMOD Best Paper Award (2016) and the Research Highlight Award (2017).

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Research interests

Agentic RAG, NL2SQL, and AI Agents OLAP algorithms and systems Query optimization

Experience

Research Scientist / Senior Technology Research Expert

Alibaba Cloud, Alibaba Group

Drove innovation from Data+AI research to production, publishing novel methods in top-tier conferences while deploying them at scale to solve key business challenges.

Researcher

Noah's Ark Lab, Huawei

Pioneered research in meta-learning and few-shot learning, validating approaches on real-world problems.

Education

PhD in Computer Science

The Hong Kong University of Science and Technology (HKUST)

Supervised by Prof. Ke Yi. Research on approximate query processing and streaming algorithms.

BS in Computer Science

Fudan University

Awards
ACM SIGMOD Research Highlight Award
ACM SIGMOD ∙ 2017
Recognized for outstanding research contribution.
ACM SIGMOD Best Paper Award
ACM SIGMOD ∙ 2016
Best paper award at the top database conference.
Featured Publications
Pengyi Wang, Sibei Chen, Ju Fan, Bin Wu, Nan Tang, Jian Tan (2025). Andromeda: Debugging Database Performance Issues with Retrieval-Augmented Large Language Models. Companion of the 2025 International Conference on Management of Data (SIGMOD 2025).
DOI
Liang Lin, Yuhan Li, Bin Wu, Huijun Mai, Renjie Lou, Jian Tan, Feifei Li (2023). Anser: Adaptive Information Sharing Framework of AnalyticDB. Proceedings of the VLDB Endowment, 16(12), 2023.
PDF DOI
Ye Li, Jian Tan, Bin Wu, Xiao He, Feifei Li (2023). ShapleyIQ: Influence Quantification by Shapley Values for Performance Debugging of Microservices. Proceedings of the 28th ACM International Conference on Architectural Support for Programming Languages and Operating Systems (ASPLOS 2023).
DOI
Han Fu, Chang Liu, Bin Wu, Feifei Li, Jian Tan, Jianling Sun (2023). CatSQL: Towards Real World Natural Language to SQL Applications. Proceedings of the VLDB Endowment, 16(6), 2023.
PDF DOI
Chuangxian Wei, Bin Wu, Sheng Wang, Renjie Lou, Chaoqun Zhan, Feifei Li, Yuanzhe Cai (2020). AnalyticDB-V: A Hybrid Analytical Engine Towards Query Fusion for Structured and Unstructured Data. Proceedings of the VLDB Endowment, 13(12), 2020.
PDF DOI
Feifei Li, Bin Wu, Ke Yi, Zhuoyue Zhao (2016). Wander Join: Online Aggregation via Random Walks. Proceedings of the 2016 International Conference on Management of Data (SIGMOD 2016).
PDF DOI
Other Publications

Note

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Qingda Hu, Xinjun Jimmy Yang, Feifei Li, Junru Li, Ya Lin, Yuqi Zhou, Yicong Zhu, Junwei Zhang, Rongbiao Xie, Ling Zhou, Bin Wu, Wenchao Zhou (2026). PolarStore: High-Performance Data Compression for Large-Scale Cloud-Native Databases. 24th USENIX Conference on File and Storage Technologies (FAST 2026).
PDF
Chunhui Shen, Qianyu Ouyang, Feibo Li, Zhipeng Liu, Longcheng Zhu, Yujie Zou, Qing Su, Tianhuan Yu, Yi Yi, Jianhong Hu, Cen Zheng, Bo Wen, Hanbang Zheng, Lunfan Xu, Sicheng Pan, Bin Wu, Xiao He, Ye Li, Jian Tan, Sheng Wang, Dan Pei, Wei Zhang, Feifei Li (2023). Lindorm TSDB: A Cloud-Native Time-Series Database for Large-Scale Monitoring Systems. Proceedings of the VLDB Endowment, 16(12), 2023.
PDF DOI
Xiao He, Jian Tan, Bin Wu, Feifei Li, Xinping Zhang, Gaozhong Liang, Jinfeng Xu (2023). Active Sampling for Sparse Table by Bayesian Optimization with Adaptive Resolution. IEEE 39th International Conference on Data Engineering (ICDE 2023).
DOI
Xiao He, Ye Li, Jian Tan, Bin Wu, Feifei Li (2023). OneShotSTL: One-Shot Seasonal-Trend Decomposition for Online Time Series Anomaly Detection and Forecasting. Proceedings of the VLDB Endowment, 16(6), 2023.
PDF Preprint DOI
Pengcheng Zhang, Bin Yao, Chao Gao, Bin Wu, Xiao He, Feifei Li, Yuanfei Lu, Chaoqun Zhan, Feilong Tang (2023). Learning-Based Query Optimization for Multi-Probe Approximate Nearest Neighbor Search. The VLDB Journal, 32(3), 2023.
PDF DOI
Yuan Qiu, Wei Dong, Ke Yi, Bin Wu, Feifei Li (2022). Releasing Private Data for Numerical Queries. Proceedings of the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022).
DOI
Qichen Wang, Chaoqi Zhang, Danish Alsayed, Ke Yi, Bin Wu, Feifei Li, Chaoqun Zhan (2021). Cquirrel: Continuous Query Processing over Acyclic Relational Schemas. Proceedings of the VLDB Endowment, 14(12), 2021.
PDF DOI
Yuan Qiu, Yilei Wang, Ke Yi, Feifei Li, Bin Wu, Chaoqun Zhan (2021). Weighted Distinct Sampling: Cardinality Estimation for SPJ Queries. Proceedings of the 2021 International Conference on Management of Data (SIGMOD 2021).
DOI
Feifei Li, Bin Wu, Ke Yi, Zhuoyue Zhao (2019). Wander Join and XDB: Online Aggregation via Random Walks. ACM Transactions on Database Systems (TODS), 44(1), 2019.
DOI
Fengwei Zhou, Bin Wu, Zhenguo Li (2018). Deep Meta-Learning: Learning to Learn in the Concept Space. arXiv preprint arXiv:1802.03596, 2018.
PDF DOI
Feifei Li, Bin Wu, Ke Yi, Zhuoyue Zhao (2017). Wander Join and XDB: Online Aggregation via Random Walks. ACM SIGMOD Record, 46(1), 2017 (Research Highlight).
DOI
Bin Wu, Ke Yi, Zhenguo Li (2016). Counting Triangles in Large Graphs by Random Sampling. IEEE Transactions on Knowledge and Data Engineering, 28(8), 2016.
DOI
Feifei Li, Bin Wu, Ke Yi, Zhuoyue Zhao (2016). Wander Join: Online Aggregation for Joins. Proceedings of the 2016 International Conference on Management of Data (SIGMOD 2016, Demo).
DOI
Xiangyang Xue, Wei Zhang, Jie Zhang, Bin Wu, Jianping Fan, Yao Lu (2011). Correlative Multi-Label Multi-Instance Image Annotation. 2011 International Conference on Computer Vision (ICCV 2011).
DOI
Wei Zhang, Xiangyang Xue, Jianping Fan, Xiaojing Huang, Bin Wu, Mingjie Liu (2011). Multi-Kernel Multi-Label Learning with Max-Margin Concept Network. IJCAI 2011.
PDF DOI